*** Appendix 10: Scaling of Composite Measures

*** Descriptive statistics

use data_wide.dta, clear
fre RT_fpnews


*** Direct effect of getting the news from Russia Today

use  data_long.dta, clear


*Last minute coding
gen pred_bundes_gov_r = (pred_bundes_gov - 1) / 10
gen pred_Russia_r = (pred_Russia - 1) / 10
recode RT_fpnews (1=0 "No RT consumer") (2=1 "RT consumer"), gen(RT_fpnews_r)


local controls1 "age female educ_secondary educ_prof_high educ_acad_high i.exp"
local controls2a "authoritarian conspiracy_sum	know_sum	pred_bundes_gov_r	pred_Russia_r	" // for total sample
local controls2b "				conspiracy_sum	know_sum	pred_bundes_gov_r	pred_Russia_r	" // for for authoritarian beliefs
local controls2c "authoritarian					know_sum	pred_bundes_gov_r	pred_Russia_r	" // for conspiracy beliefs
local controls2d "authoritarian conspiracy_sum				pred_bundes_gov_r	pred_Russia_r	" // for knowledge
local controls2e "authoritarian conspiracy_sum know_sum 						pred_Russia_r	" // for att twd German gov
local controls2f "authoritarian conspiracy_sum know_sum		pred_bundes_gov_r					" // for att twd Russia



*Average effect, all experiments
mixed poolexp i.treat_exp `controls1' `controls2a' i.RT_fpnews_r || lfdn:

*Interaction model
mixed poolexp i.treat_exp##i.RT_fpnews_r `controls1' `controls2a'  || lfdn:
margins, dydx(2.treat_exp 3.treat_exp 4.treat_exp 5.treat_exp) at(RT_fpnews_r=(1 0))


*Without substantive controls
mixed poolexp i.treat_exp `controls1' i.RT_fpnews || lfdn:
mixed poolexp i.treat_exp##i.RT_fpnews_r `controls1'  || lfdn:
margins, dydx(2.treat_exp 3.treat_exp 4.treat_exp 5.treat_exp) at(RT_fpnews_r=(1 0))

